IBM's Big Data Strategy: Combine And Conquer

Big Blue is gobbling up big data companies at a steady clip. What's the method behind the madness?

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IBM has been on a big data buying binge in recent years, acquiring more than 11 companies in the data analytics space since 2008, including six firms over the past 12 months. Just last week Big Blue announced it had completed yet another acquisition: StoredIQ, an Austin, Texas-based developer of analysis and management software for managing litigation and regulation requirements.

"Our goal is to offer the broadest and biggest depth and breadth of any vendor in the marketplace," Kopp told InformationWeek in a phone interview. "As we fill up this portfolio, we're really filling in the holes that we had in (our) integration."

With its recent acquisitions, IBM has focused on companies and products that can help it deliver "smarter analytics," including improved simplicity and integration of various software components that mix well with the company's big data offerings.

"When you think about the challenges of big data, you have to drive back to what is motivating people to invest in more data structures, and that's really the goal of smarter analytics," said Kopp.

IBM's big data tools, including InfoSphere Data Explorer, which is based on technology from the company's Vivismo acquisition, as well as Star Analytics, another recent purchase, are designed to make data easier to access and manage.

"StoredIQ, for example, "has a very strong focus on simplifying storage administration in the world of big data," said Kopp. The product also helps companies automate the elimination of data that they're not going to leverage.

Kopp claimed IBM's big data products are superior to those of its top competitors.

"When you look at how we compare to, say, Oracle or Teradata, they are starting to build out some capabilities, but not to the degree that we have within (our) ecosystems," she said.

Specifically, Kopp said the data virtualization capabilities and explorations of IBM's Vivismo, as well as the integration features of its InfoSphere DataStage, provide enterprises with a more comprehensive big data solution.

Customers "not only need all the parts and pieces, but they also need the parts and pieces integrated," she added. "That's the key."

"We're working with several universities to drive better curriculums, because these people (data scientists) aren't born. They're going to have to be created," she said

For instance, IBM has increased its efforts to bring big data to academia. In the past 18 months, the company has built new partnerships with Michigan State, Northwestern University, Yale and the University of Southern California. The company's' goal is to help develop courses that provide the analytics skills required for big data platforms.

On the applications side, Kopp named IBM's InfoSphere BigInsights as a good example of a software tool that simplifies Hadoop and big data app development.

"There's a very strong focus on managing the simplicity of the system," said Kopp of BigInsights. "You can get immediate value with some visualization around the data -- without the data scientist."

There's no doubt Google has made headway into businesses: Just 28 percent discourage or ban use of its productivity ­products, and 69 percent cite Google Apps' good or excellent ­mobility. But progress could still stall: 59 percent of nonusers ­distrust the security of Google's cloud. Its data privacy is an open question, and 37 percent worry about integration.

IT’s tried for years to simplify business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.